pharmaceutics Article Role of IL6R Genetic Variants in Predicting Response to Tocilizumab in Patients with Rheumatoid Arthritis Luis Sainz 1,2,3,† , Pau Riera 3,4,5, *,† , Patricia Moya 1,3 , Sara Bernal 3,5,6 , Jordi Casademont 2,3,7 , Cesar Díaz-Torné 1,2,3 , Ana Milena Millán 1,3 , Hye Sang Park 1,3 , Adriana Lasa 3,5,6 and Héctor Corominas 1,2,3, * 1 Rheumatology Department, Hospital de la Santa Creu i Sant Pau, 08041 Barcelona, Spain 2 Department of Medicine, Universitat Autònoma de Barcelona (UAB), 08193 Barcelona, Spain 3 Institut d’Investigació Biomèdica Sant Pau (IIB SANT PAU), 08041 Barcelona, Spain 4 Pharmacy Department, Hospital de la Santa Creu i Sant Pau, 08025 Barcelona, Spain 5 CIBER de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, 28029 Madrid, Spain 6 Genetics Department, Hospital de la Santa Creu i Sant Pau, 08025 Barcelona, Spain 7 Internal Medicine Department, Hospital de la Santa Creu i Sant Pau, 08025 Barcelona, Spain * Correspondence: priera@santpau.cat (P.R.); hcorominas@santpau.cat (H.C.) † These authors contributed equally to this work. Abstract: Rheumatoid arthritis (RA) is a prevalent autoimmune disease characterized by chronic arthritis that may lead to irreversible joint damage and significant disability. Patients with RA are commonly treated with Tocilizumab (TCZ), an IL-6 receptor (IL-6R) antagonist, but many patients refractorily respond to this therapy. Identifying genetic biomarkers as predictors of TCZ response could be a key to providing a personalized medicine strategy. We aimed to evaluate whether Citation: Sainz, L.; Riera, P.; Moya, P.; functional single nucleotide polymorphisms (SNPs) in the IL6R gene could predict TCZ response in Bernal, S.; Casademont, J.; patients with RA. We retrospectively included 88 RA patients treated with TCZ. Six SNPs previously Díaz-Torné, C.; Millán, A.M.; Park, described in the IL6R gene (rs12083537, rs11265618, rs4329505, rs2228145, rs4537545, and rs4845625) H.S.; Lasa, A.; Corominas, H. Role of were genotyped in DNA samples from these patients. Using parametric tests, we evaluated the IL6R Genetic Variants in Predicting association between these polymorphisms and clinicopathological features. Responses to treatments Response to Tocilizumab in Patients were assessed at six months using three variables: a quantitative improvement in Disease activity with Rheumatoid Arthritis. Pharmaceutics 2022, 14, 1942. score including 28 joints (DAS28), a satisfactory European League Against Rheumatism (EULAR) https://doi.org/10.3390/ response, and low disease activity (LDA) achievement. The three response variables studied were pharmaceutics14091942 associated with genetic variant rs4845625, and no association was found with the other five SNPs. Our findings support the potential clinical value of SNPs in the IL6R gene as predictive biomarkers Academic Editors: Francisco for TCZ response. Abad Santos and Pablo Zubiaur Received: 15 July 2022 Keywords: IL6R; genetic variants; tocilizumab; rheumatoid arthritis; predictive factors Accepted: 30 August 2022 Published: 14 September 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in 1. Introduction published maps and institutional affil- Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease with iations. an estimated worldwide prevalence ranging from 0.2 to 1% [1]. The most recent estimate in adults in Spain, published in 2016, reported a prevalence of 0.82% (95% CI, 0.59–1.15) [2]. RA etiology is complex as it involves the interplay of environmental triggers and geno- type, factors known to play an important role in RA physiopathology. The most relevant Copyright: © 2022 by the authors. genes associated with RA are involved in immunity activation and regulation, antigenic Licensee MDPI, Basel, Switzerland. presentation, and proinflammatory cytokines [3]. RA is characterized by synovial inflam- This article is an open access article mation, hyperplasia, and the progressive destruction of bones and cartilages in multiple distributed under the terms and joints [3]. If not treated correctly, these characteristics cause progressive disability, sys- conditions of the Creative Commons temic complications, and reduced life expectancy [4]. Over the last 20 years, treatment has Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ changed substantially thanks to the development of targeted biologic and non-biologic 4.0/). Pharmaceutics 2022, 14, 1942. https://doi.org/10.3390/pharmaceutics14091942 https://www.mdpi.com/journal/pharmaceutics Pharmaceutics 2022, 14, 1942 2 of 9 disease-modifying anti-rheumatic drugs. These high-efficacy therapies enabled the im- proved control of the disease, and their diverse mechanisms of action, targeting various immune pathways, broadened the treatment armamentarium. Therapeutic strategies have also changed. Focus is now centered on early treatments and a treat-to-target approach where the main therapeutic goal is to achieve remissions or low disease activity (LDA) in order to prevent structural damage and maintain a quality of life [5–10]. The choice of treatments for RA is currently a trial-and-error process as no consistent clinical, biochemical, or genetic biomarkers that predict response to biological disease- modifying anti-rheumatic drug (bDMARD) have yet been identified. As delays in finding effective treatment can lead to disease progression and a poorer quality of life, establishing biomarkers of different responses is of paramount importance [11–13]. Because genetics can explain much of the inter-individual response to treatments, the study of single nucleotide polymorphisms (SNPs) has gained increasing interest in recent years. In the field of phar- macogenomics, such research has focused on genetic biomarkers relative to MTX [14–17] and anti-tumor necrosis factor (anti-TNF) treatments [18–24]. Tocilizumab (TCZ) is a first-line bDMARD that competitively inhibits the binding of interleukin-6 (IL-6) to its soluble or membrane receptor (IL-6R). It is effective in the treat- ment of patients with moderate to severe RA and European League Against Rheumatism (EULAR) response rates of between 62 and 80 [13,25–27]. Nevertheless, due to pharma- coeconomic considerations, it is generally only prescribed after an inadequate response to methotrexate (MTX) or anti-TNF agents ([28–30]). Despite the effectiveness of TCZ in RA [13], some patients do not respond adequately to this drug. Taking into account that TCZ blocks the action of IL-6R, we hypothesized that functional variations in this gene could affect TCZ effectiveness. Previous studies assessed the influence of IL6R ge- netic variants on TCZ responses. However, the results hitherto published are inconsistent and produce contradictory results, and they are, therefore, not applicable to clinical prac- tice [31–35]. The aim of the present study was to evaluate whether genetic variants in the IL6R gene are associated with responses to TCZ in patients with RA. 2. Materials and Methods 2.1. Study Population We conducted a retrospective cohort study that included 88 RA patients treated with TCZ between 2016 and 2021. The following sociodemographic and clinical data were collected from electronic medical records: age, gender, age at diagnosis, previous treatments, comorbidities, TCZ starting date, TCZ dose, administration route, concomitant treatments, C-reactive protein (CRP), rheumatoid factor (RF), anti-citrullinated protein antibody (ACPA), DAS28 at treatment initiation and at 6 months, and EULAR response at 6 months. DAS28 is a simplified disease activity score frequently used in trials and clinical practice that includes counting tender and swollen joints, the general health state evaluated by the patient, and acute phase reactants in blood tests. Response variables were determined at the baseline and at 6 months of TCZ treatment. Responses to treatment were assessed using three variables: a quantitative improvement in DAS28, a satisfactory EULAR response, and low disease activity (LDA). According to the EULAR guidelines, we considered a EULAR response to be satisfactory when the DAS28 improvement was greater than 1.2 and the presented DAS28 was lower than 3.2. We considered LDA when patients reached a DAS28 lower than 3.2 at 6 months [36,37]. The study was approved by the institutional ethics committees and registered at clinicaltrials.gov (protocol code: IIBSP-IIL-2020-148). All participants provided written informed consent for blood sampling and genetic analyses. 2.2. Genetic Studies SNPs were selected according to published data concerning their functional relevance in the IL6 receptor. Those included were rs12083537, rs11265618, rs4329505, rs2228145, rs4537545 and rs4845625 (Table 1). The rationale for the selection of these SNPs was detailed Pharmaceutics 2022, 14, 1942 3 of 9 in previous studies [31–34,38]. All SNPs presented a minor allele frequency (MAF) over 0.10 in European population according to the ALFA project [39]. Table 1. Selected functional polymorphisms in the IL6R gene. refSeg Genomic Position (GRCh38) MAF Alleles rs12083537 chr1:154408627 0.21 A>G rs11265618 chr1:154457616 0.17 C>T rs4329505 chr1:154459944 0.17 T>C rs2228145 chr1:154454494 0.40 A>C rs4537545 chr1:154446403 0.41 C>T rs4845625 chr1:154449591 0.43 T>C Abbreviations: IL6R, Interleukin 6 Receptor; MAF, minor allele frequency reported in the European population. The minor allele is highlighted in bold. Genomic DNA was automatically extracted from peripheral whole-blood samples (Autopure, Qiagen, Hilden, Germany). SNPs were analyzed by real-time PCR using Taq- Man SNP genotyping assays (Applied Biosystems, Foster City, CA, USA). The IDs for each Taqman SNP assays were the following: rs12083537 (C_30997483_10), rs11265618 (C_30997439_10), rs4329505 (C_26292281_20), rs2228145 (C_16170664_10), and rs4537545 (C_11258666_20). A custom Taqman assay was used for rs4845625. All cases were success- fully genotyped. Statistical Analyses The Hardy–Weinberg equilibrium was assessed for each analyzed SNP using a chi- square test. Codominant, dominant, and recessive models of inheritance were considered to assess associations with outcome variables whenever appropriate. Quantitative data were expressed as the mean (SD) for normally distributed variables. Normality was assessed using the Shapiro–Wilk test. The Student’s t-test or ANOVA was applied for normally distributed variables depending on the number of groups compared. We analysed the bivariate association for qualitative dichotomous variables using Pearson’s χ2 or Fisher’s exact test. Associations between the various SNPs and the qualitative response variables were tested using χ2 tests. All tests were two-sided and a significance level of 5% (α = 0.05) was considered significant. All statistical analyses were performed using IBM-SPSS (version 26.0, IBM, Armonk, NY, USA). 3. Results 3.1. Characteristics of the Patients We studied 88 patients with RA diagnosed at a mean age of 46.6 years (SD 15.86). Mean disease duration was 16.5 (SD 11.9) years. Most patients were female (86.4%). Table 2 summarizes baseline demographic and clinical characteristics. The mean numbers of conventional cDMARD and bDMARD treatments received prior to TCZ were 2.39 (SD 1.3) and 1.48 (SD 1.4), respectively. Baseline disease activity, measured by DAS28, was high, with a mean of 5.4 (SD 0.9). We were unable to include 4 of the 88 patients (4.5%) because the treatment was dis- continued prematurely due to a loss of follow-up in 3 patients and the observation of a hypersensitivity reaction in 1 patient. Thus, these patients were not included in the efficacy analysis. After 6 months, the mean decrease in DAS28 was 2.9 (SD 1.3) and the satisfactory EULAR response rate was 73.9%. None of the response variables studied showed statistically significant differences according to sex, tobacco exposure, seropositivity, the number of previous cDMARD or bDMARD, age at diagnosis, and body mass index (BMI). However, we observed two trends concerning these variables: EULAR satisfactory responses were higher in women than in Pharmaceutics 2022, 14, 1942 4 of 9 men (79.7% vs. 60%, p = 0.16) and non-smokers showed a trend towards greater DAS28 improvements than smokers (3.04 vs. 2.35, p = 0.08). Table 2. Baseline patient characteristics (n = 88). Variables n (%) Mean (SD) Female/Male 76 (86.4)/12 (13.6) Age at diagnosis (years) 46.57 (15.86) Disease duration (years) 16.53 (11.87) Erosive RA 47 (53.4) RF positive 58 (65.9) ACPA positive 57 (64.8) Smoking habit Non-smoker 61 (69.3) Ex-smoker 14 (15.9) Smoker 13 (14.8) Body mass index 28.64 (6.07) Number of previous cDMARD 2.39 (1.32) Number of previous bDMARD 1.48 (1.41) TCZ administration (intravenous) 47 (53.4) Baseline DAS28-CRP 5.39 (0.98) ACPA, anticitrullinated protein antibodies; CRP, C-reactive protein; DAS28-CRP, disease activity score includ- ing 28 joints (based on CRP); bDMARD, biological disease-modifying antirheumatic drug; ESR, erythrocyte sedimentation rate; RF, rheumatoid factor; SD, standard deviation; TCZ, tocilizumab. 3.2. Genetic Determinants and Response to Treatment The genotypic frequencies of the six SNPs studied were in Hardy–Weinberg equilib- rium. As expected from the allele frequency population-based studies, we found that the mutated allele (C) of the SNP rs4845625 was more frequent than the wild-type (T) [39]. In the univariate analysis, only one SNP, rs4845625, showed a statistically significant association with the response outcomes studied (Table 3). When considering DAS28 im- provement, six months after initiating TCZ treatment, we observed differences between the three genotypes compatible with an additive genetic model. The TT carriers for rs4845625 had a greater decrease (3.62) in DAS28 than those with the CT genotype (3.06) and the CC genotype (2.36) (p = 0.015). Table 3. Associations between the considered SNPs and response outcomes at 6 months. SNPs Genotype (n) DAS28 Improvement Satisfactory EULAR Response Rates Low Disease Activity Rates Mean Abso- Genetic Genetic Genetic p % OR (95% CI) p % OR (95% CI) p lute Value Model Model Model T/T (13) 3.62 Cod 0.015 92.3 Cod - 0.01 90.9 Cod - 0.015 rs4845625 T/C (42) 3.07 Rec 0.009 85.7 Rec 4.83 (1.63–14.28) 0.03 85.4 Rec 4.95 (1.57 −15.55) 0.004 C/C (29) 2.36 58.6 56.5 C/C (57) 3.06 Cod 0.16 82.5 Cod - 0.271 81.1 Cod - 0.474 rs11265618 C/T (24) 2.66 Dom 0.115 66.7 Dom 2.35 (0.82–6.71) 0.106 68.4 Dom 2.01 (0.65–6.22) 0.223 T/T (3) 1.76 66.7 66.7 T/T (58) 3 Cod 0.106 82.8 Cod - 0.212 81.5 Cod - 0.388 rs4329505 T/C (23) 2.56 Dom 0.06 65.2 Dom 2.54 (0.88–7.29) 0.078 66.7 Dom 2.2 (0.7–6.8) 0.169 C/C (3) 1.76 66.7 66.7 A/A (55) 2.94 Cod 0.717 78.2 Cod - 0.335 81.6 Cod - 0.454 rs12083537 A/G (24) 2.76 Dom 0.749 70.8 Dom 0.88 (0.3–2.54) 0.809 68.2 Dom 1.98 (0.66–5.95) 0.222 G/G (5) 3.38 100.0 75.0 A/A (25) 3.01 Cod 0.483 80.0 Cod - 0.888 78.3 Cod - 0.841 rs2228145 A/C (44) 2.99 Dom 0.651 77.3 Dom 0.8 (0.26–2.54) 0.709 78.9 Dom 1.08 (0.33–3.52) 0.898 C/C (15) 2.55 73.3 71.4 C/C (24) 2.98 Cod 0.702 83.3 Cod - 0.666 81.8 Cod - 0.690 rs4537545 C/T (46) 2.97 Dom 0.759 76.1 Dom 0.6 (0.18–2.04) 0.410 77.5 Dom 1.46 (0.42–5.1) 0.550 T/T (14) 2.64 77.4 69.2 Cod: Codominant; DAS28: disease activity score including 28 joints; Dom: dominant; OR: odds ratio; p: p-value; Rec: recessive; SNPs: single nucleotide polymorphisms. Significant values are highlighted in bold. Pharmaceutics 2022, 14, 1942 5 of 9 Patients carrying the T allele (TT + CT) also reached more satisfactory EULAR response rates than CC carriers (87.3% vs. 58.6%, p = 0.03). Accordingly, when assessing LDA rates, the TT and CT genotypes also demonstrated better outcomes (86.5% vs. 56.6%, p = 0.04. OR (95% CI) = 4.95 (1.5–15.56)). We did not perform a multivariate analysis as there were no statistically significant associations that could act as confounding variables. As for the other five SNPs studied, no statistically significant associations were found (Table 3). The results showed a trend towards an association with response variables for rs4329505 and rs11265618, although they did not reach statistical significance. Patients carrying the CC genotype for rs4329505 seemed to have a poorer reduction in DAS28 at 6 months than those with the TT + CT genotypes (1.76 vs. 2.95, p = 0.06). For the rs11265618 variant, the CC genotype (dominant homozygous) appeared to have superior satisfactory EULAR response rates than CT + TT genotypes (82.5% vs. 66.7%, p = 0.106). 4. Discussion In this study, we assessed the associations between six SNPs in the IL6R gene and the response outcomes at 6 months in patients with RA. We found an association between rs4845625 and the three response variables used: DAS28 improvement, EULAR response, and LDA achievement. As far as we know, this is the first study to show that rs4845625 could be a potential biomarker of response to TCZ in RA patients. Our results suggest that patients carrying TT and TC genotypes present higher satisfactory EULAR response rates when treated with tocilizumab (85.7–92.3% compared to the 73.9% of the whole cohort). However, larger prospective studies are needed to validate our results and for implementing rs4845625 genotyping in clinical practice. This SNP is located at Chr1 (q21.3) g.154422067 in intron 7 of the IL6R gene. In silico tools such as the ESE Finder predict that this SNP could alter the splicing process and, therefore, modify the final amount of a functional protein. However, further analyses are required to confirm this hypothesis. Current evidence shows several associations between rs4845625 and inflammatory pathways. Shah T et al. reported that rs4845625 is associated with plasma concentrations of IL6. However, the contribution of the SNPs evaluated in plasma IL6 levels in their study was mild [40]. Associations of the allele rs4845625*T with increased levels of RCP, LDL, and apolipoprotein B were also found in a healthy cohort of 995 participants [38]. These results contrast with our findings of improved response outcomes in T allele carriers. A possible explanation for this discrepancy could be that a patient with a genetically determined pro-inflammatory basal state would have a greater chance to respond to treatments blocking these pathways. However, studies are lacking regarding associations between this genotype and inflammatory markers in the context of autoimmune diseases. Rs4845625 genetic variants have been linked to cardiovascular conditions in several reports, suggesting an important role of the IL-6 pathway ([41–44]), but we did not find previous research regarding rs4845625 and RA. Although the rs11265618 polymorphism in our study showed no statistically signifi- cant association with the response to treatment variables, we observed a trend towards a greater response of the homozygous genotype (CC). In 2018, Maldonado-Montoro et al. de- scribed an association within the CC genotype that showed a better response in terms of LDA after 12 months of TCZ therapy (OR (95% CI) = 12.11 (2.2–67.8)), but they were unable to demonstrate this regarding the EULAR response or the DAS28 improvement [31]. While our findings did not confirm previously reported results, we propose that further investigations and larger samples are needed to determine the potential usefulness of rs11265618 as a biomarker for TCZ therapy. Our results regarding rs4329505 also merit discussion. Despite the lack of statistical significance, our results using an additive genetic model suggest that the T allele could be associated with DAS28 improvements. Similar results have been reported previously. In a Pharmaceutics 2022, 14, 1942 6 of 9 retrospective study including 79 RA patients, the CC genotype of rs4329505 was linked to a poorer response regarding less joint swelling at 3 months [33]. Supporting the biologic role of these SNP variants with inflammatory physiopathological pathways in autoimmune diseases, the CC genotype has shown an association with higher RCP levels in female diabetic patients. Interestingly, these changes were independent of IL-6 serum levels and were not observed in healthy individuals [45]. However, the study by Maldonado-Montoro et al. and the findings reported by Luxembourger et al. did not suggest that rs4329505 could predict responses to TCZ [31,34]. Overall, data supporting the role of rs4329505 genetic polymorphisms in the response to treatment with TCZ in RA patients are scarce and inconsistent, even though our findings seem to indicate a trend worth investigating in future studies. We did not find any associations between rs12083537, rs2228145, and rs4537545 genetic variants and the response to treatment outcomes. Diverse and conflicting results have been reported concerning the rs12083537 AA genotype. This variant was initially associated with a worse response when considering swollen joint count individually and when analyzed as a haplotype along with rs2228145 and rs4329505 variants [33]. In contrast, Maldonado- Montoro et al. and Luxembourger et al. reported improved responses to TCZ in the rs12083537 AA genotype when analyzing LDA at 12 months and EULAR response rates at 6 months, respectively [31,34]. These conflicting data contrast with the absence of associations in our study. Apart from the study by Enevold et al., there were no further reports of associations between rs2228145 and the response to TCZ in RA [33]. In contrast, possible physiopathological mechanisms of rs2228145 have been reproduced, suggesting a regulation of IL-6 bioactivity via the downregulation of cellular IL-6R [46,47]. Among the published studies about TCZ pharmacogenetics, we found only one study that followed a genome-wide association studies (GWAS) approach, which could be useful for avoiding missing potential biomarkers. However, none of the eight loci encountered clearly seemed to be involved in the physiopathology of RA or IL-6 pathways [35]. The inconsistent findings between studies and the lack of a robust biological basis on the most frequently reported SNP highlight the complexity of immune pathways in RA and the factors that modulate responses to TCZ. The limitations of this study should be considered when interpreting results. First, the retrospective design and the relatively small sample size may have compromised potential associations between SNPs and response to TCZ. In particular, rs11265618 and rs4329505 homozygosity for the mutated allele is expected to be low, as mutated allele frequencies are 0.03 and 0.04. Nonetheless, the homogeneity of our cohort supports the validity of our findings. Second, as the present study was designed to study promising IL6R SNPs, we may not have detected other genetic variants as potential predictors to TCZ treatments. Further research in the pharmacogenomics of RA treatment is needed to establish robust evidence with clinical relevance that could lead to personalized medicine. In addition, further studies are needed to investigate the potential use of rs4845625 as a treatment biomarker of TCZ. 5. Conclusions Our results suggest that the IL6R polymorphism, rs4845625, is associated with DAS28 improvements, EULAR response rates, and an LDA at 6 months after initiating TCZ in RA patients. Author Contributions: Conceptualization, L.S., P.R., P.M., S.B., C.D.-T., A.L. and H.C.; methodology, L.S., P.R., P.M., S.B., H.S.P., A.L. and H.C.; validation, P.R., P.M., S.B., A.L., J.C. and H.C.; investigation, L.S. and P.R.; resources, S.B. and A.L.; writing—original draft preparation, L.S. and P.R.; writing— review and editing, P.M., S.B., J.C., H.C., C.D.-T., A.L., A.M.M., H.S.P., A.L. and H.C.; visualization, L.S. and P.R.; supervision, P.M., S.B., A.L., H.C. and J.C.; project administration, L.S. and P.R.; funding acquisition, L.S. All authors have read and agreed to the published version of the manuscript. Pharmaceutics 2022, 14, 1942 7 of 9 Funding: This research was supported in part by Beca STADA 2020-2021, given by “Societat Catalana de Reumatologia”. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research Ethics Committee of “Hospital de la Santa Creu I Sant Pau” (IIBSP-IIL-2020-148; 1 March 2021). Informed Consent Statement: Informed consent was obtained from all patients involved in the study. Data Availability Statement: The data presented in this study are available upon request from the corresponding author. The data are not publicly available due to the inclusion of clinical and personal information. Acknowledgments: We thank Carolyn Newey for language editing. We thank Ivan Castellví, Lidia González-Quereda, Berta Magallares, Ana Laiz, Helena Codes, and David Lobo Prat for their revisions on the final work. We thank Ignasi Gich for statistical analysis. We thank Meritxell Cros for helping in the genotyping process. Conflicts of Interest: Pau Riera received a travel grant from Roche. H.C. has received grants for research and attendance at conferences from Grünenthal, MSD, Biogen, Galapagos, Roche, BMS, and honorarium for advisory boards from Galapagos, Gebro, Abbvie, Sanofi, and UCB. The other authors declare no conflict of interest. References 1. Cross, M.; Smith, E.; Hoy, D.; Carmona, L.; Wolfe, F.; Vos, T.; Williams, B.; Gabriel, S.; Lassere, M.; Johns, N.; et al. The global burden of rheumatoid arthritis: Estimates from the Global Burden of Disease 2010 study. Ann. Rheum. Dis. 2014, 73, 1316–1322. [CrossRef] [PubMed] 2. Seoane-Mato, D.; Sánchez-Piedra, C.; Silva-Fernández, L.; Sivera, F.; Blanco, F.J.; Ruiz, F.P.; Juan-Mas, A.; Pego-Reigosa, J.M.; Narváez, J.; Martí, N.Q.; et al. Prevalence of rheumatic diseases in adult population in Spain (EPISER 2016 study): Aims and methodology. Reumatol. Clin. 2019, 15, 90–96. [CrossRef] [PubMed] 3. McInnes, I.B.; Schett, G. The Pathogenesis of Rheumatoid Arthritis. N. Engl. J. Med. 2011, 365, 2205–2219. [CrossRef] 4. Rodríguez-Valverde, V.; Cáliz, R.C.; Álvaro, J.M.-G.; de la Fuente, J.L.M.; Mendoza, J.M.; Molina, J.T.; Sánchez, J.A.; García, F.B.; Gualda, E.B.; Crespillo, J.C.; et al. III Actualización del Consenso de la Sociedad Española de Reumatología sobre terapia biológica en la artritis reumatoide. Reumatol. Clin. 2006, 2, S52–S59. [CrossRef] 5. Goekoop-Ruiterman, Y.P.; De Vries-Bouwstra, J.K.; Allaart, C.F.; Van Zeben, D.; Kerstens, P.J.; Hazes, J.M.W.; Zwinderman, A.H.; Peeters, A.J.; De Jonge-Bok, J.M.; Mallée, C.; et al. Comparison of treatment strategies in early rheumatoid arthritis: A randomized trial. Ann. Intern. Med. 2007, 146, 406–415. [CrossRef] [PubMed] 6. Saunders, S.A.; Capell, H.A.; Stirling, A.; Vallance, R.; Kincaid, W.; McMahon, A.D.; Porter, D.R. Triple therapy in early active rheumatoid arthritis: A randomized, single-blind, controlled trial comparing step-up and parallel treatment strategies. Arthritis Care Res. 2008, 58, 1310–1317. [CrossRef] 7. Möttönen, T.; Hannonen, P.; Korpela, M.; Nissilä, M.; Kautiainen, H.; Ilonen, J.; Laasonen, L.; Kaipiainen-Seppänen, O.; Franzen, P.; Helve, T.; et al. Delay to Institution of Therapy and Induction of Remission Using Single-Drug or Combination-Disease-Modifying Antirheumatic Drug Therapy in Early Rheumatoid Arthritis. Arthritis Care Res. 2002, 46, 894–898. [CrossRef] 8. Verstappen, S.M.M.; Jacobs, J.W.G.; van der Veen, M.J.; Heurkens, A.H.M.; Schenk, Y.; ter Borg, E.J.; Blaauw, A.A.M.; Bijlsma, J.W.J. Computer Assisted Management in Early Rheumatoid Arthritis (CAMERA, an open-label strategy trial). Ann. Rheum. Dis. 2007, 66, 1443–1449. [CrossRef] 9. Grigor, C.; Capell, H.; Stirling, A.; McMahon, A.D.; Lock, P.; Vallance, R.; Porter, D.; Kincaid, W. Effect of a treatment strategy of tight control for rheumatoid arthritis (the TICORA study): A single-blind randomised controlled trial. Lancet 2004, 364, 263–269. [CrossRef] 10. Smolen, J.S.; Landewé, R.B.M.; Bijlsma, J.W.J.; Burmester, G.R.; Dougados, M.; Kerschbaumer, A.; McInnes, I.B.; Sepriano, A.; van Vollenhoven, R.F.; de Wit, M.; et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Ann. Rheum. Dis. 2020, 79, 685–699. [CrossRef] 11. Pers, Y.-M.; Fortunet, C.; Constant, E.; Lambert, J.; Godfrin-Valnet, M.; De Jong, A.; Mercier, G.; Prades, B.P.; Wendling, D.; Gaudin, P.; et al. Predictors of response and remission in a large cohort of rheumatoid arthritis patients treated with tocilizumab in clinical practice. Rheumatology 2013, 53, 76–84. [CrossRef] [PubMed] 12. Tarnowski, M.; Paradowska-Gorycka, A.; Dabrowska-Zamojcin, ˛ E.; Czerewaty, M.; Słuczanowska-Głabowska, ˛ S.; Pawlik, A. The effect of gene polymorphisms on patient responses to rheumatoid arthritis therapy. Expert Opin. Drug Metab. Toxicol. 2016, 12, 41–55. [CrossRef] [PubMed] 13. Narváez, J.; Magallares, B.; Torné, C.D.; Hernández, M.V.; Reina, D.; Corominas, H.; Sanmartí, R.; Llobet, J.M.; de la Serna, A.R.; Nolla, J.M. Predictive factors for induction of remission in patients with active rheumatoid arthritis treated with tocilizumab in clinical practice. Semin. Arthritis Rheum. 2015, 45, 386–390. [CrossRef] [PubMed] Pharmaceutics 2022, 14, 1942 8 of 9 14. Cao, M.; Guo, M.; Wu, D.-Q.; Meng, L. Pharmacogenomics of Methotrexate: Current Status and Future Outlook. Curr. Drug Metab. 2018, 19, 1182–1187. [CrossRef] [PubMed] 15. Salazar, J.; Moya, P.; Altés, A.; Díaz-Torné, C.; Casademont, J.; Cerdà-Gabaroi, D.; Corominas, H.; Baiget, M. Polymorphisms in genes involved in the mechanism of action of methotrexate: Are they associated with outcome in rheumatoid arthritis patients? Pharmacogenomics 2014, 15, 1079–1090. [CrossRef] 16. Moya, P.; Salazar, J.; Arranz, M.J.; Díaz-Torné, C.; del Río, E.; Casademont, J.; Corominas, H.; Baiget, M. Methotrexate phar- macokinetic genetic variants are associated with outcome in rheumatoid arthritis patients. Pharmacogenomics 2016, 17, 25–29. [CrossRef] 17. Jekic, B.; Maksimovic, N.; Damnjanovic, T.; Biljana, J.; Nela, M.; Tatjana, D. Methotrexate pharmacogenetics in the treatment of rheumatoid arthritis. Pharmacogenomics 2019, 20, 1235–1245. [CrossRef] 18. Márquez, A.; Ferreiro-Iglesias, A.; Dávila-Fajardo, C.L.; Montes, A.; Pascual-Salcedo, D.; Perez-Pampin, E.; Moreno-Ramos, M.J.; García-Portales, R.; Navarro, F.; Moreira, V.; et al. Lack of validation of genetic variants associated with anti-tumor necrosis factor therapy response in rheumatoid arthritis: A genome-wide association study replication and meta-analysis. Arthritis Res. Ther. 2014, 16, R66. [CrossRef] 19. Sode, J.; Vogel, U.; Bank, S.; Andersen, P.S.; Hetland, M.L.; Locht, H.; Heegaard, N.H.H.; Andersen, V. Genetic Variations in Pattern Recognition Receptor Loci Are Associated with Anti-TNF Response in Patients with Rheumatoid Arthritis. PLoS ONE 2015, 10, e0139781. [CrossRef] 20. Bek, S.; Bojesen, A.B.; Nielsen, J.V.; Sode, J.; Bank, S.; Vogel, U.; Andersen, V. Systematic review and meta-analysis: Pharmacoge- netics of anti-TNF treatment response in rheumatoid arthritis. Pharm. J. 2017, 17, 403–411. [CrossRef] 21. Wysocki, T.; Paradowska-Gorycka, A. Pharmacogenomics of Anti-TNF Treatment Response Marks a New Era of Tailored Rheumatoid Arthritis Therapy. Int. J. Mol. Sci. 2022, 23, 2366. [CrossRef] [PubMed] 22. Montes, A.; Perez-Pampin, E.; Joven, B.; Carreira, P.; Fernández-Nebro, A.; Ordóñez, M.D.C.; Navarro-Sarabia, F.; Moreira, V.; Vasilopoulos, Y.; Sarafidou, T.; et al. FCGR polymorphisms in the treatment of rheumatoid arthritis with Fc-containing TNF inhibitors. Pharmacogenomics 2015, 16, 333–345. [CrossRef] 23. Chen, W.; Xu, H.; Wang, X.; Gu, J.; Xiong, H.; Shi, Y. The tumor necrosis factor receptor superfamily member 1B polymorphisms predict response to anti-TNF therapy in patients with autoimmune disease: A meta-analysis. Int. Immunopharmacol. 2015, 28, 146–153. [CrossRef] [PubMed] 24. Canet, L.M.; Filipescu, I.; Cáliz, R.; Lupiañez, C.B.; Canhão, H.; Escudero, A.; Segura-Catena, J.; Soto-Pino, M.J.; Ferrer, M.A.; García, A.; et al. Genetic variants within the TNFRSF1B gene and susceptibility to rheumatoid arthritis and response to anti-TNF drugs: A multicenter study. Pharm. Genom. 2015, 25, 323–333. [CrossRef] [PubMed] 25. Iking-Konert, C.; Von Hinüber, U.; Richter, C.; Schwenke, H.; Gürtler, I.; Kästner, P.; Klapperich, B.; Peters, A.M.; Burmester, G.-R. ROUTINE-a prospective, multicentre, non-interventional, observational study to evaluate the safety and effectiveness of intra- venous tocilizumab for the treatment of active rheumatoid arthritis in daily practice in Germany Rheumatology key messages. Rheumatology 2015, 55, 624–635. [CrossRef] [PubMed] 26. Forsblad-D’Elia, H.; Bengtsson, K.; Kristensen, L.E.; Jacobsson, L.T.H. Drug adherence, response and predictors thereof for tocilizumab in patients with rheumatoid arthritis: Results from the Swedish biologics register. Rheumatology 2014, 54, 1186–1193. [CrossRef] 27. Backhaus, M.; Kaufmann, J.; Richter, C.; Wassenberg, S.; Roske, A.-E.; Hellmann, P.; Gaubitz, M. Comparison of tocilizumab and tumour necrosis factor inhibitors in rheumatoid arthritis: A retrospective analysis of 1603 patients managed in routine clinical practice. Clin. Rheumatol. 2015, 34, 673–681. [CrossRef] 28. Scott, L.J. Tocilizumab: A Review in Rheumatoid Arthritis. Drugs 2017, 77, 1865–1879. [CrossRef] 29. Gabay, C.; Emery, P.; van Vollenhoven, R.; Dikranian, A.; Alten, R.; Pavelka, K.; Klearman, M.; Musselman, D.; Agarwal, S.; Green, J.; et al. Tocilizumab monotherapy versus adalimumab monotherapy for treatment of rheumatoid arthritis (ADACTA): A randomised, double-blind, controlled phase 4 trial. Lancet 2013, 381, 1541–1550. [CrossRef] 30. Jones, G.; Wallace, T.; McIntosh, M.J.; Brockwell, L.; Gómez-Reino, J.J.; Sebba, A. Five-year Efficacy and Safety of Tocilizumab Monotherapy in Patients with Rheumatoid Arthritis Who Were Methotrexate- and Biologic-naive or Free of Methotrexate for 6 Months: The AMBITION Study. J. Rheumatol. 2016, 44, 142–146. [CrossRef] 31. Maldonado-Montoro, M.; Cañadas-Garre, M.; González-Utrilla, A.; Calleja-Hernández, M. Influence of IL6R gene polymorphisms in the effectiveness to treatment with tocilizumab in rheumatoid arthritis. Pharm. J. 2016, 18, 167–172. [CrossRef] [PubMed] 32. Maldonado-Montoro, M.; Cañadas-Garre, M.; González-Utrilla, A.; Plaza-Plaza, J.C.; Calleja-Hernández, M. Genetic and clinical biomarkers of tocilizumab response in patients with rheumatoid arthritis. Pharmacol. Res. 2016, 111, 264–271. [CrossRef] [PubMed] 33. Enevold, C.; Baslund, B.; Linde, L.; Josephsen, N.L.; Tarp, U.; Lindegaard, H.; Jacobsen, S.; Nielsen, C.H. Interleukin-6-receptor polymorphisms rs12083537, rs2228145, and rs4329505 as predictors of response to tocilizumab in rheumatoid arthritis. Pharm. Genom. 2014, 24, 401–405. [CrossRef] [PubMed] 34. Luxembourger, C.; Ruyssen-Witrand, A.; Ladhari, C.; Rittore, C.; Degboe, Y.; Maillefert, J.-F.; Gaudin, P.; Marotte, H.; Wendling, D.; Jorgensen, C.; et al. A single nucleotide polymorphism of IL6-receptor is associated with response to tocilizumab in rheumatoid arthritis patients. Pharm. J. 2019, 19, 368–374. [CrossRef] Pharmaceutics 2022, 14, 1942 9 of 9 35. Wang, J.; Bansal, A.T.; Martin, M.A.; Germer, S.; Benayed, R.; Essioux, L.; Lee, J.S.; Begovich, A.B.; Hemmings, A.; Kenwright, A.; et al. Genome-wide association analysis implicates the involvement of eight loci with response to tocilizumab for the treatment of rheumatoid arthritis. Pharm. J. 2012, 13, 235–241. [CrossRef] 36. van Gestel, A.M.; Anderson, J.J.; van Riel, P.L.; Boers, M.; Haagsma, C.J.; Rich, B.; Wells, G.; Lange, M.L.; Felson, D.T. ACR and EULAR improvement criteria have comparable validity in rheumatoid arthritis trials. American College of Rheumatology European League of Associations for Rheumatology. J. Rheumatol. 1999, 26, 705–711. 37. Aletaha, D.; Ward, M.M.; Machold, K.; Nell, V.P.K.; Stamm, T.; Smolen, J.S. Remission and active disease in rheumatoid arthritis: Defining criteria for disease activity states. Arthritis Care Res. 2005, 52, 2625–2636. [CrossRef] 38. Arguinano, A.A.; Naderi, E.; Ndiaye, N.C.; Stathopoulou, M.; Dadé, S.; Alizadeh, B.; Visvikis-Siest, S. IL6R haplotype rs4845625*T/rs4537545*C is a risk factor for simultaneously high CRP, LDL and ApoB levels. Genes Immun. 2017, 18, 163–169. [CrossRef] 39. Phan, L.; Jin, Y.; Zhang, H.; Qiang, W.; Shekhtman, E.; Shao, D.; Revoe, D.; Villamarin, R.; Ivanchenko, E.; Kimura, M.; et al. ‘ALFA: Allele Frequency Aggregator.’ National Center for Biotechnology Information, U.S. National Library of Medicine. Available online: www.ncbi.nlm.nih.gov/snp/docs/gsr/alfa/ (accessed on 10 March 2020). 40. Shah, T.; Zabaneh, D.; Gaunt, T.; Swerdlow, D.; Shah, S.; Talmud, P.; Day, I.N.; Whittaker, J.; Holmes, M.V.; Sofat, R.; et al. Gene-Centric Analysis Identifies Variants Associated with Interleukin-6 Levels and Shared Pathways with Other Inflammation Markers. Circ. Cardiovasc. Genet. 2013, 6, 163–170. [CrossRef] 41. Webb, T.R.; Erdmann, J.; Stirrups, K.E.; Stitziel, N.O.; Masca, N.G.D.; Jansen, H.; Kanoni, S.; Nelson, C.P.; Ferrario, P.G.; König, I.R.; et al. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease. J. Am. Coll. Cardiol. 2017, 69, 823–836. [CrossRef] 42. Wu, G.; Cheng, M.; Huang, H.; Yang, B.; Jiang, H.; Huang, C. A Variant of IL6R Is Associated with the Recurrence of Atrial Fibrillation after Catheter Ablation in a Chinese Han Population. PLoS ONE 2014, 9, e99623. [CrossRef] 43. Deloukas, P.; Kanoni, S.; Willenborg, C.; Farrall, M.; Assimes, T.L.; Thompson, J.R.; Ingelsson, E.; Saleheen, D.; Erdmann, J.; Goldstein, B.A.; et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat. Genet. 2013, 45, 25–33. [CrossRef] [PubMed] 44. Svensson, T.; Kitlinski, M.; Engström, G.; Melander, O. A genetic risk score for CAD, psychological stress, and their interaction as predictors of CAD, fatal MI, non-fatal MI and cardiovascular death. PLoS ONE 2017, 12, e0176029. [CrossRef] [PubMed] 45. Qi, L.; Rifai, N.; Hu, F.B. Interleukin-6 Receptor Gene, Plasma C-Reactive Protein, and Diabetes Risk in Women. Diabetes 2009, 58, 275–278. [CrossRef] [PubMed] 46. Ferreira, R.C.; Freitag, D.F.; Cutler, A.; Howson, J.; Rainbow, D.B.; Smyth, D.; Kaptoge, S.; Clarke, P.; Boreham, C.; Coulson, R.M.; et al. Functional IL6R 358Ala Allele Impairs Classical IL-6 Receptor Signaling and Influences Risk of Diverse Inflammatory Diseases. PLoS Genet. 2013, 9, e1003444. [CrossRef] [PubMed] 47. Reich, D.; Patterson, N.; Ramesh, V.; De Jager, P.L.; McDonald, G.J.; Tandon, A.; Choy, E.; Hu, D.; Tamraz, B.; Pawlikowska, L.; et al. Admixture Mapping of an Allele Affecting Interleukin 6 Soluble Receptor and Interleukin 6 Levels. Am. J. Hum. Genet. 2007, 80, 716–726. [CrossRef]